Skip to main content
NCBI home page
G3: Genes | Genomes | Genetics logoLink to G3: Genes | Genomes | Genetics
. 2021 May 11;11(7):jkab165. doi: 10.1093/g3journal/jkab165

An age-downregulated ribosomal RpS28 protein variant regulates the muscle proteome

Jianqin Jiao 1, Kanisha Kavdia 2, Vishwajeeth Pagala 2, Lance Palmer 3, David Finkelstein 3, Yiping Fan 3, Junmin Peng 1,2, Fabio Demontis 1,✉
Editor: M Ramaswami
PMCID: PMC8495913  PMID: 33974070

Abstract

Recent evidence indicates that the composition of the ribosome is heterogeneous and that multiple types of specialized ribosomes regulate the synthesis of specific protein subsets. In Drosophila, we find that expression of the ribosomal RpS28 protein variants RpS28a and RpS28-like preferentially occurs in the germline, a tissue resistant to aging and that it significantly declines in skeletal muscle during aging. Muscle-specific overexpression of RpS28a at levels similar to those seen in the germline decreases early mortality and promotes the synthesis of a subset of proteins with known anti-aging roles, some of which have preferential expression in the germline. These findings indicate a contribution of specialized ribosomal proteins to the regulation of the muscle proteome during aging.

Keywords: aging, ribosome, protein translation, Drosophila, germline, skeletal muscle

Introduction

Protein translation is increasingly recognized as an important regulator of aging. Signaling pathways that increase overall protein synthesis promote aging, whereas interventions that reduceprotein synthesis extend lifespan and delay multiple aspects of tissue aging across species (Mehta et al. 2010).

The ribosome is the central regulator of protein synthesis, and knockdown of core ribosomal proteins delays aging by decreasing overall protein synthesis, which in turn can induce adaptive stress responses and improve proteostasis (Hansen et al. 2007; Steffen and Dillin 2016).

Recently, it was found that the core proteins composing the ribosome are heterogeneous and that multiple versions of the ribosome are present within an organism and even within a single cell (Shi et al. 2017). Such specialized subpopulations of ribosomes have been proposed to preferentially promote the synthesis of specific proteins (Xue and Barna 2012; Filipovska and Rackham 2013).

An example of specialized mRNA translation became apparent from analysis of RpL38 mutant mice. Such mice do not display any substantial change in the rate of development or body size, indicating that RPL38 is not required for maintaining overall protein synthesis. However, ribosomes lacking RPL38 are inefficient at translating a subset of Hox mRNAs, leading to developmental patterning defects of the skeleton (Kondrashov et al. 2011).

Another example of specialized mRNA translation is evident in yeast ribosomes that incorporate RpL7b, RpL12a, RpL22b, and RpL18a ribosomal protein variants but are incapable of translating ASH1 mRNA. However, ASH1 protein synthesis occurs when paralog ribosomal proteins are incorporated into the ribosomes (Komili et al. 2007).

Altogether, evidence that specialized ribosomes can customize protein synthesis is growing, but a comprehensive understanding of this phenomenon is missing (Xue and Barna 2012; Filipovska and Rackham 2013). Moreover, it is unknown whether the abundance of specialized ribosomes changes with aging or whether such ribosomes regulate any aspect of aging.

Materials and methods

qPCR

Total RNA was extracted with the TRIzol reagent (Life Technologies) from at least 30 thoraces from male flies per group, followed by cleanup with the RNeasy kit (QIAGEN) and on-column DNase digestion. Total RNA was reverse transcribed with the iScript cDNA synthesis kit (Bio-Rad). qRT-PCR was performed with the iQ SYBR Green Supermix and a CFX96 Real-Time PCR Detection System (Bio-Rad). Alpha-Tubulin 84B was used as a normalization reference. These data were further normalized by the average gene expression of all ribosomal proteins in the same group (i.e., RpS or RpL genes). Relative quantitation of mRNA levels was determined with the comparative CT method. The list of ribosomal proteins was obtained from FlyBase (www.flybase.org) and the RPG database (Nakao et al. 2004).

Cloning and fly transgenesis

The coding sequences of Drosophila RpS28a and RpS28-like were cloned into the pUAST-attB vector with EcoRI and XbaI restriction enzymes. The resulting vectors were sequenced to ensure the absence of mutations and injected into w1118;attP2; embryos via phiC31-mediated transgenesis.

Fly stocks

The O1, B3, UAS-foxo, UAS-Mnt, and Mhc-Gal4 fly stocks have been previously described (Demontis and Perrimon 2010; Demontis et al. 2014; Parkhitko et al. 2016; Hunt et al. 2019).

Lifespan analysis

For survival analysis, male flies were collected within 24 h from eclosion and reared at standard density (25 per vial) on cornmeal/soy flour/yeast fly food at 25°C and 60% humidity. Dead flies were counted every 2 days and the food was changed.

To rule out any variation from cytoplasmic background effects, all crosses were set up with female virgins from the w1118;Mhc-Gal4. To avoid any contribution of genetic background mutations to the observed lifespan phenotypes, UAS-RpS28a and UAS-RpS28-like transgenes were injected into a w1118 background, and each line was maintained as a mixed population of isogenic siblings carrying either a UAS- or no transgene (distinguished by eye color: white+ and white−, respectively). Male siblings carrying either a UAS- or no transgene and having the same genetic background were then crossed to homozygous w1118;Mhc-Gal4 (rosy+ white−) females and the resulting male progenies were sorted (based on eye color) into isogenic transgene-expressing and transgene-nonexpressing cohorts before lifespan analysis. UAS- transgene expression obtained with Mhc-Gal4 was confirmed by qRT-PCR from fly thoraces, which consist mostly of skeletal muscle.

Proteome profiling by TMT-LC/LC-MS/MS

The analysis was performed essentially following our previously optimized method (Bai et al. 2017). Drosophila thoraces, consisting mostly of skeletal muscle, were lysed by a denaturing 8 M urea-based buffer. Specifically, ∼20 mg of tissue was lysed with ∼400 µl of the lysis buffer in a NextAdvance bullet blender at 4°C, with addition of ∼200 µl of glass beads. The lysate was further centrifuged to remove any remaining cuticle fragments. Protein concentration was determined in the resulting supernatant by a previously described short gel-based staining method (Xu et al. 2009). Each sample was digested and desalted, followed by TMT labeling. The labeled samples were equally mixed and fractionated by basic pH reverse-phase liquid chromatography (LC). The LC fractions were collected and further analyzed by acidic pH reverse-phase LC-MS/MS. During ion fragmentation, the TMT regents were cleaved to produce reporter ions for quantification. The collected raw MS data were searched against a database to identify peptides using a hybrid search engine (Wang et al. 2014b). While the peptides were identified by MS/MS, the quantification was achieved by the fragmented reporter ions in the same MS/MS scans. The peptide quantification data were then corrected for mixing errors and summarized to derive protein quantification results. Statistical analysis (ANOVA) was performed to determine cutoff for altered proteins (Niu et al. 2017).

Computational analyses of mRNA features

A table linking transcript IDs to gene IDs for Drosophila genes was obtained from ftp://ftp.flybase.net/releases/current/precomputed_files/genes/fbgn_fbtr_fbpp_fb_2016_04.tsv.gz. Gene sequences were downloaded from the UCSC Genome Browser table browser (Karolchik et al. 2004) after selecting the ensGene table from the Ensembl Genes track. 5ʹ UTR, CDS and 3ʹ UTR sequences were separately downloaded. The genes were also split into lists according to their increased translation in response to RpS28a. The 5ʹ UTR, CDS, and 3ʹ UTR sequences for the genes in each of these lists were analyzed for GC content and length. The results were loaded into R software (v3.2.2) and plotted in boxplots using ggplot. Analysis for motif enrichment was performed with DREME, Discriminative Regular Expression Motif Elicitation (http://meme-suite.org/tools/dreme).

Statistical analyses

Statistical analysis was performed with Excel and the GraphPad Prism software. Unpaired two-tailed Student’s t-test was used to compare the means of two independent groups with each other.

OASIS (https://sbi.postech.ac.kr/oasis/surv/) and the Fisher’s Exact Test were used for the statistical analysis of lifespan data.

Data availability

The authors affirm that all data necessary for confirming the conclusions of the article are present within the article, figures, Supplemental figures, and Supplementary tables. The mass-spectrometry data are provided in Supplementary Table S1. Other primary data are provided in Supplementary Table S2. Supplementary files are available at figshare: https://doi.org/10.25387/g3.14515938.

Results

Expression of RpS28a and RpS28-like declines during skeletal muscle aging

Ribosomes have long been proposed to undergo senescence (Miquel and Johnson 1979) but it is currently unknown whether their composition changes with aging, as observed in other developmental and disease contexts (Filipovska and Rackham 2013).

To determine whether the expression of ribosomal proteins changes with aging in Drosophila, we profiled the expression of components of the 60S large and 40S small ribosomal subunits by qPCR in skeletal muscle, a major tissue for lifespan determination (Demontis and Perrimon 2010; Demontis et al. 2013; Hunt et al. 2021; Rai et al. 2021). The expression of most genes encoding ribosomal proteins remained relatively constant in both young and old flies but the mRNA levels of RpL10Aa, RpS28a, and RpS28-like significantly declined with aging (Figure 1A and Supplementary Figure S1).

Figure 1.

Figure 1

Open in a new tab

Role of germline- and age-regulated ribosomal RpS28 proteins in longevity. (A) Age-associated changes in ribosomal RpS gene expression. Old versus young fold change in RpS gene expression reveals a significant decline in RpS28a and RpS28-like gene expression (n = 4; *P < 0.05; **P < 0.01). ModEncode tissue expression data are reported for a panel of Drosophila tissues and developmental stages (see legend of Supplementary Figure S1 for complete listing), including the expression in the germline (ovary and testis; black box), and RNAseq data for skeletal muscle (blue box). Low (yellow) to high (red) expression is indicated. (B) RpS28a and RpS28-like ribosomal genes are more highly expressed at both young and old age (1 and 6 weeks) in the long-lived O1 Drosophila strain (yellow), obtained from multiple rounds of selection for postponed senescence from the B3 strain (grey; n = 4, with *P < 0.05, **P < 0.01, and ***P < 0.001). RpS28a expression also increases in response to the activity of the anti-aging FoxO and Mnt transcription factors (n = 4, with *P < 0.05, **P < 0.01, and ***P < 0.001), whereas RpS28-like levels are not modulated. (C) RpS28a extends lifespan. RpS28a overexpression in skeletal muscle with the UAS/Gal4 system and the muscle-specific Mhc-Gal4 driver results in muscle levels of RpS28a closer to those seen in the germline (n = 4, ***P < 0.001) and in increased survival in the first half of the lifespan, compared with isogenic controls (P-value at 25% <0.0001, Fisher’s Exact test; RpS28aOE: Mhc>RpS28a, n = 492; isogenic control: Mhc>+, n = 465). Reduced early mortality upon RpS28a overexpression was also seen in another independent trial (Supplementary Figure S3). (D) RpS28-like overexpression at levels similar to those in the germline (n = 4, ***P < 0.001) does not regulate lifespan, as compared with isogenic controls (control: Mhc>+, n = 147; RpS28-likeOE: Mhc>RpS28-like, n = 75).

Expression of RpS28a and RpS28-like is enriched in the germline vs somatic tissues and increases in response to anti-aging interventions

Previous studies have suggested that ribosome heterogeneity may arise from changes in the expression of ribosomal protein variants in different cell types and developmental stages (Xue and Barna 2012; Filipovska and Rackham 2013). Therefore, we interrogated the ModEncode gene expression dataset to define whether age-regulated ribosomal proteins also have a distinct pattern of tissue expression in Drosophila. Interestingly, whereas most ribosomal proteins were highly expressed in all tissues, the ribosomal protein variants RpS28a and RpS28-like were preferentially expressed in the germline (testis) and had low expression in somatic tissues (Figure 1A). Importantly, RpS28a and RpS28-like have high sequence similarity with the more highly expressed RpS28b protein (Supplementary Figure S2), suggesting that these alternative RpS28 variants may substitute for RpS28b in ribosome assembly. Altogether, these findings suggest that subpopulations of ribosomes comprising RpS28a and/or RpS28-like are relatively more abundant in the germline than in somatic tissues and that their expression declines during aging in muscle.

Previous studies have shown that the germline is a tissue resistant to aging at least in part due to its increased capacity to maintain proteostasis and mount stress responses (Smelick and Ahmed 2005; Curran et al. 2009). For example, reduction in insulin-like signaling causes activation of the transcription factor FOXO and the somatic misexpression of the germline genes pie-1 and pgl in the C. elegans intestine. In turn, somatic cells with acquired germline characteristics are protected from genotoxic stress (Curran et al. 2009).

Because the Drosophila germline had higher RpS28a and RpS28-like expression than did somatic tissues (Figure 1A), we asked whether these ribosomal proteins, which are also age-downregulated, are differentially expressed in fly strains with distinct lifespans. To this purpose, we analyzed the mRNA levels of RpS28a and RpS28-like in muscle tissue from the B3 and O1 Drosophila lines. The O1 line was derived from the B3 line via multiple rounds of selection for negligible senescence (Rose 1984; Wilson et al. 2006) and displays a ∼75% increase in the median lifespan (Hunt et al. 2019). Interestingly, O1 flies express higher levels of RpS28a and RpS28-like than do B3 flies at both young and old age (Figure 1B), suggesting that these alternative ribosomal components may contribute to the extreme longevity of the O1 strain. Moreover, overexpression of the transcription factors foxo and Mnt in muscle, which increases lifespan in Drosophila (Demontis and Perrimon 2010; Demontis et al. 2014), significantly promoted the expression of RpS28a, whereas RpS28-like mRNA levels were unaffected (Figure 2B). Altogether, these findings suggest that anti-aging pathways may extend lifespan by altering the expression of ribosomal protein variants.

Figure 2.

Figure 2

Open in a new tab

Specialized regulation of protein synthesis by RpS28a. (A) RpS28a overexpression (OE) increases overall protein content in skeletal muscle when compared with isogenic controls (P < 0.05; control: Mhc>+, n = 4; RpS28aOE: Mhc>RpS28a, n = 3). (B) RpS28a overexpression induces proteomic changes limited to a subset of proteins. A significance score, defined as –log10(P-value) is indicated. (C) RpS28a overexpression induces an increase in the synthesis of several proteins of which half have preferential or enriched expression in the germline (testis and/or ovary; purple). As expected, RpS28a overexpression increased RpS28a protein levels. Percent increase in protein levels is indicated (P < 0.05; control: Mhc>+, n = 4; RpS28aOE: Mhc>RpS28a, n = 3). (D) RpS28a overexpression increases the synthesis of several proteins which have been implicated in anti-aging responses (P < 0.05). The full mass-spectrometry data are provided in Supplementary Table S1.

Muscle-specific RpS28a overexpression improves early survival during aging

To test the hypothesis that RpS28a and RpS28-like ribosomal proteins delay aging, we employed the UAS/Gal4 system and the muscle-specific Mhc-Gal4 driver to increase RpS28a expression in skeletal muscle to levels similar to those seen in the germline (Figure 1C). Compared with isogenic siblings with no transgene expression, flies with muscle-specific RpS28a overexpression exhibited increased survival in the first half of their lifespan (Figure 1C and Supplementary Figure S3). In contrast, RpS28-like overexpression did not extend lifespan (Figure 1D). These findings suggest that RpS28a-containing ribosomes may have unique properties that delay early mortality during aging.

Previous studies have shown that an overall reduction in protein synthesis delays aging across species (Mehta et al. 2010; Demontis et al. 2014). Therefore, RpS28a may delay aging by contributing to the assembly of specialized ribosomes with reduced capacity for overall protein synthesis. To test this hypothesis, we analyzed the total protein content of muscle with RpS28a overexpression and found it to be significantly higher than in controls (Figure 2A). This suggests that RpS28a overexpression promotes protein synthesis rather than decreasing it, which we also observed with RpS28-like overexpression (Supplementary Figure S4). This finding is in line with the observation that RpS28 is indeed necessary for rRNA processing and ribosome assembly (Robledo et al. 2008; Gripp et al. 2014; Kim et al. 2017). Therefore, a mechanism other than reduction in protein synthesis must be responsible for the anti-aging effects of RpS28a.

Muscle-specific RpS28a overexpression increases the protein levels of a subset of proteins, some of which are germline-enriched and/or have anti-aging functions

Previous studies in yeast have shown that mutations in RpS28 influence translation accuracy (Anthony and Liebman 1995) suggesting that, despite their high sequence homology (Supplementary Figure S2), RpS28 variants may confer distinct accuracy to protein synthesis and consequently regulate lifespan. However, additional anti-aging effects of RpS28a-containing ribosomes are also possible, including the preferential synthesis of specific protein subsets. To test this hypothesis, TMT mass-spectrometry was utilized to profile the proteomic changes induced in skeletal muscle by RpS28a overexpression. Overall, 5951 proteins were detected, of which 494 were significantly regulated (P < 0.05; Figure 2B and Supplementary Table S1). Analysis of a more stringent set of 128 regulated proteins (P < 0.05 and >20% change) indicated that RpS28a promotes the synthesis of a subset of 114 proteins whereas only 14 proteins had lower levels in response to RpS28a overexpression (Figure 2B and Supplementary Table S1). Therefore, a primary effect of RpS28a is to promote the synthesis of a subset of proteins. Consultation of the ModEncode tissue expression dataset revealed that 9 out of the 18 most upregulated proteins (P < 0.05 and >50% change) had preferential or enriched expression in the Drosophila germline (testis and/or ovary; Figure 2C), suggesting that RpS28a reinforces the synthesis of a subset of germline proteins (Figure 2C).

To better understand whether RpS28a-mediated translational regulation is responsible for the effect of RpS28a on lifespan determination, we next examined whether proteins upregulated by RpS28a have been implicated in aging. Interestingly, some Rps28a-upregulated proteins are known to contribute to several protective responses (Figure 2D) that delay aging and extend lifespan, including preservation of mitochondrial function and integrity (CG5776/SPATA5; CG14757/succinate dehydrogenase assembly factor), stress resistance (CoRest/REST corepressor; GstD1 and GstD10/glutathione S-transferase D1 and D10), DNA repair (tefu/ATM kinase; MRG15/NuA4 complex subunit), protein degradation (Atg8a/autophagy-specific gene 8a; CG8539/carboxypeptidase A2; Uch-L3/26S proteasome regulatory complex subunit p37A), and energy homeostasis (CG5144/creatine kinase). These findings indicate that RpS28a may delay aging by promoting the synthesis of a subset of proteins with anti-aging functions (Figure 2D).

RpS28 is part of the translation initiation complex of eukaryotic ribosomes and is located at the ribosome’s exit site, in which it interacts with the 5ʹ UTR of the mRNA initiating translation (Pisarev et al. 2008; Anger et al. 2013). Specialized ribosomes with different RpS28 protein variants may therefore have a propensity to translate mRNAs with specific features, as observed for other specialized ribosomes (Xue and Barna 2012; Filipovska and Rackham 2013).

To investigate the basis of preferential protein translation following RpS28a overexpression, the GC content and length of the 5ʹ UTR, coding sequence, and 3ʹ UTR of the mRNAs corresponding to the upregulated proteins were compared with those of all detected proteins. However, the GC content and length were not significant different (Supplementary Figure S5). Further analyses identified two motifs that were significantly enriched in the 3ʹ UTR of the mRNAs corresponding to RpS28a-upregulated proteins (Supplementary Figure S5). The 3ʹ UTR is known to regulate translational efficiency via multiple mechanisms, including mRNA circularization and interaction between the 3ʹ UTR and 5ʹ UTR (Mazumder et al. 2003), suggesting that RpS28a-containing ribosomes may more efficiently translate mRNAs with certain 3ʹ UTR features.

Discussion

In this study, we have found that the expression of some ribosomal proteins varies during skeletal muscle aging in Drosophila. RpS28a and RpS28-like are the only components of the small ribosomal subunit that decline with aging, suggesting that these RpS28 ribosomal protein variants may contribute to aging. Whereas RpS28-like overexpression does not impact lifespan, we find that RpS28a overexpression in skeletal muscle reduces mortality in the first half of the lifespan. Interestingly, other genes have been previously found to promote survival in the first part of the lifespan without impacting later mortality in C. elegans (Wang et al. 2014a), suggesting that RpS28a activity in muscle induces a similar response.

Although many mechanisms may explain the impact of RpS28a on aging, we have found that RpS28a overexpression changes the levels of a subset of proteins (494), some of which have known anti-aging roles. Apart from RpS28a, no other ribosomal proteins were upregulated in muscle with RpS28a overexpression (Supplementary Table S1) but most RpS28a-induced changes consisted of upregulated proteins (450), which may contribute to explain the increase in protein levels seen in response to RpS28a overexpression, in addition to the capacity of RpS28 to promote rRNA processing and ribosome assembly (Robledo et al. 2008; Gripp et al. 2014; Kim et al. 2017).

Because RpS28a is a ribosomal protein, it is possible that proteomic changes observed upon its overexpression stem from its direct role in promoting the preferential translation of certain mRNAs. Alternatively, they may derive from indirect effects of Rps28a overexpression on other cellular processes that regulate protein levels, such as protein degradation. Moreover, although we have found preferential enrichment of certain motifs in the mRNAs that encode for RpS28a-upregulated proteins, their significance remains undetermined and experimental testing of such mRNA motifs will be needed to assess whether they are necessary for RpS28a-mediated modulation of mRNA translation.

Several RpS28a-upregulated proteins and RpS28a itself are preferentially expressed in the germline compared to somatic tissues. On this basis, it is possible that expression of RpS28a in the germline may help increase the levels of proteins that define this tissue and its capacity to resist aging.

In summary, this study identifies a previously unanticipated role for age-downregulated Rps28a in regulating the levels of a subset of proteins with known anti-aging roles in skeletal muscle.

Acknowledgments

The authors thank Michelle Curley and Maricela Robles-Murguia for technical help.

Funding

This work was supported by research grants to F.D. from the American Federation for Aging Research, the Glenn Foundation for Medical Research, the Ellison Medical Foundation (New Scholar in Aging award), the American Parkinson Disease Association, the Hartwell Foundation (Individual Biomedical Research award), and the National Institute on Aging of the NIH (R01AG055532 and R56AG063806). The mass-spectrometry analysis was performed in the St. Jude Children’s Research Hospital Proteomics Facility, partially supported by NIH Cancer Center Support grant P30CA021765 and by NIH grant R01AG047928 (J.P.). Research at St. Jude Children’s Research Hospital is supported by the ALSAC. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Conflicts of interest

None declared.

Literature cited

  1. Anger AM, Armache JP, Berninghausen O, Habeck M, Subklewe M, et al. 2013. Structures of the human and Drosophila 80S ribosome. Nature. 497:80–85. [DOI] [PubMed] [Google Scholar]
  2. Anthony RA, Liebman SW.. 1995. Alterations in ribosomal protein RPS28 can diversely affect translational accuracy in Saccharomyces cerevisiae. Genetics. 140:1247–1258. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bai B, Tan H, Pagala VR, High AA, Ichhaporia VP, et al. 2017. Deep profiling of proteome and phosphoproteome by isobaric labeling, extensive liquid chromatography, and mass spectrometry. Methods Enzymol. 585:377–395. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Curran SP, Wu X, Riedel CG, Ruvkun G.. 2009. A soma-to-germline transformation in long-lived Caenorhabditis elegans mutants. Nature. 459:1079–1084. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Demontis F, Patel VK, Swindell WR, Perrimon N.. 2014. Intertissue control of the nucleolus via a myokine-dependent longevity pathway. Cell Rep. 7:1481–1494. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Demontis F, Perrimon N.. 2010. FOXO/4E-BP signaling in Drosophila muscles regulates organism-wide proteostasis during aging. Cell. 143:813–825. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Demontis F, Piccirillo R, Goldberg AL, Perrimon N.. 2013. The influence of skeletal muscle on systemic aging and lifespan. Aging Cell. 12:943–949. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Filipovska A, Rackham O.. 2013. Specialization from synthesis: how ribosome diversity can customize protein function. FEBS Lett. 587:1189–1197. [DOI] [PubMed] [Google Scholar]
  9. Gripp KW, Curry C, Olney AH, Sandoval C, Fisher J, et al. ; UW Center for Mendelian Genomics. 2014. Diamond-Blackfan anemia with mandibulofacial dystostosis is heterogeneous, including the novel DBA genes TSR2 and RPS28. Am J Med Genet A Genet. 164:2240–2249. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Hansen M, Taubert S, Crawford D, Libina N, Lee SJ, et al. 2007. Lifespan extension by conditions that inhibit translation in Caenorhabditis elegans. Aging Cell. 6:95–110. [DOI] [PubMed] [Google Scholar]
  11. Hunt LC, Jiao J, Wang YD, Finkelstein D, Rao D, et al. 2019. Circadian gene variants and the skeletal muscle circadian clock contribute to the evolutionary divergence in longevity across Drosophila populations. Genome Res. 29:1262–1276. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Hunt LC, Schadeberg B, Stover J, Haugen B, Pagala V, et al. 2021. Antagonistic control of myofiber size and muscle protein quality control by the ubiquitin ligase UBR4 during aging. Nat Commun. 12:1418. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Karolchik D, Hinrichs AS, Furey TS, Roskin KM, Sugnet CW, et al. 2004. The UCSC Table Browser data retrieval tool. Nucleic Acids Res. 32:D493–D496. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Kim HK, Fuchs G, Wang S, Wei W, Zhang Y, et al. 2017. A transfer-RNA-derived small RNA regulates ribosome biogenesis. Nature. 552:57–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Komili S, Farny NG, Roth FP, Silver PA.. 2007. Functional specificity among ribosomal proteins regulates gene expression. Cell. 131:557–571. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Kondrashov N, Pusic A, Stumpf CR, Shimizu K, Hsieh AC, et al. 2011. Ribosome-mediated specificity in Hox mRNA translation and vertebrate tissue patterning. Cell. 145:383–397. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Mazumder B, Seshadri V, Fox PL.. 2003. Translational control by the 3 '-UTR: the ends specify the means. Trends Biochem Sci. 28:91–98. [DOI] [PubMed] [Google Scholar]
  18. Mehta R, Chandler-Brown D, Ramos FJ, Shamieh LS, Kaeberlein M.. 2010. Regulation of mRNA translation as a conserved mechanism of longevity control. Adv Exp Med Biol. 694:14–29. [DOI] [PubMed] [Google Scholar]
  19. Miquel J, Johnson JE Jr.. 1979. Senescent changes in the ribosomes of animal cells in vivo and in vitro. Mech Ageing Dev. 9:247–266. [DOI] [PubMed] [Google Scholar]
  20. Nakao A, Yoshihama M, Kenmochi N.. 2004. RPG: the ribosomal protein gene database. Nucleic Acids Res. 32(Database issue):D168–D170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Niu M, Cho JH, Kodali K, Pagala V, High AA, et al. 2017. Extensive peptide fractionation and y1 ion-based interference detection method for enabling accurate quantification by isobaric labeling and mass spectrometry. Anal Chem. 89:2956–2963. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Parkhitko AA, Binari R, Zhang N, Asara JM, Demontis F, et al. 2016. Tissue-specific down-regulation of S-adenosyl-homocysteine via suppression of dAhcyL1/dAhcyL2 extends health span and life span in Drosophila. Genes Dev. 30:1409–1422. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Pisarev AV, Kolupaeva VG, Yusupov MM, Hellen CU, Pestova TV.. 2008. Ribosomal position and contacts of mRNA in eukaryotic translation initiation complexes. EMBO J. 27:1609–1621. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Rai M, Coleman Z, Curley M, Nityanandam A, Platt A, et al. 2021. Proteasome stress in skeletal muscle mounts a long-range protective response that delays retinal and brain aging. Cell Metab. Mar 23:S1550-4131(21)00112-1. doi: 10.1016/j.cmet.2021.03.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Robledo S, Idol RA, Crimmins DL, Ladenson JH, Mason PJ, et al. 2008. The role of human ribosomal proteins in the maturation of rRNA and ribosome production. RNA. 14:1918–1929. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Rose MR. 1984. Laboratory evolution of postponed senescence in Drosophila melanogaster. Evolution. 38:1004–1010. [DOI] [PubMed] [Google Scholar]
  27. Shi Z, Fujii K, Kovary KM, Genuth NR, Rost HL, et al. 2017. Heterogeneous ribosomes preferentially translate distinct subpools of mRNAs genome-wide. Mol Cell. 67:71–83.e7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Smelick C, Ahmed S.. 2005. Achieving immortality in the C. elegans germline. Ageing Res Rev. 4:67–82. [DOI] [PubMed] [Google Scholar]
  29. Steffen KK, Dillin A.. 2016. A ribosomal perspective on proteostasis and aging. Cell Metab. 23:1004–1012. [DOI] [PubMed] [Google Scholar]
  30. Wang MC, Oakley HD, Carr CE, Sowa JN, Ruvkun G.. 2014a. Gene pathways that delay Caenorhabditis elegans reproductive senescence. PLoS Genet. 10:e1004752. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Wang X, Li Y, Wu Z, Wang H, Tan H, et al. 2014b. JUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy. Mol Cell Proteomics. 13:3663–3673. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Wilson RH, Morgan TJ, Mackay TF.. 2006. High-resolution mapping of quantitative trait loci affecting increased life span in Drosophila melanogaster. Genetics. 173:1455–1463. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Xu P, Duong DM, Peng J.. 2009. Systematical optimization of reverse-phase chromatography for shotgun proteomics. J Proteome Res. 8:3944–3950. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Xue S, Barna M.. 2012. Specialized ribosomes: a new frontier in gene regulation and organismal biology. Nat Rev Mol Cell Biol. 13:355–369. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The authors affirm that all data necessary for confirming the conclusions of the article are present within the article, figures, Supplemental figures, and Supplementary tables. The mass-spectrometry data are provided in Supplementary Table S1. Other primary data are provided in Supplementary Table S2. Supplementary files are available at figshare: https://doi.org/10.25387/g3.14515938.

Articles from G3: Genes|Genomes|Genetics are provided here courtesy of Oxford University Press

RESOURCES